yogeshphalak,Yogesh Ganesh Phalak,github

Hello there, I'm Yogesh Phalak 👋

I'm a PhD student in engineering mechanics at Virginia Tech, with a background in electrical and electronics engineering. My research interests revolve around using theoretical mechanics, design, and mathematics to create innovative solutions for engineering problems.

One of the things I love doing is working on robotics projects. I've been fortunate enough to work on a variety of them, ranging from localization of aerial robots to designing legged and snake robots. I find these projects fascinating because they combine elements from different disciplines, and require a lot of creativity and problem-solving skills.

Current Work

Currently, I'm working on some exciting projects:

Modeling dynamic systems with non-holonomic constraints and studying their chaotic behavior. 🌀
Exploring different complex mechanical system networks and finding intersections between them and physical reservoir computing models. 🤯
Modeling snake locomotion and exploring the role of normal force modulation in it. 🐍

Goals for 2023

My goals for this year are ambitious, but I'm excited about them. First, I want to complete my master's degree in engineering mechanics and finish my thesis on modeling animal locomotion. Second, I plan to pursue a master's degree in mathematics, because I believe that mathematics is a key element in solving many engineering problems. Finally, I hope to find a great topic for my doctoral research.

Expertise

🚀 My expertise lies in several areas of robotics, including motion planning, control, perception, and machine learning.

📈 In mathematics, I have a good background in pure mathematics and applied areas such as linear algebra, optimization, and numerical analysis.

Collaboration

If you're interested in my work, or if you'd like to collaborate, please don't hesitate to reach out. I'm always happy to chat! 😇

Fun Fact

🎨 Drawing portraits is my favorite way to unwind and tap into my creative side. When I'm not working on robotics or mathematics, you can find me sketching away!

Connect with me:

Languages and Tools:

Yogesh Ganesh Phalak's Projects

autonomous-delivery-robot

Repository for Autonomous Delivery Robot project of IvLabs, VNIT

aws-sdk-cpp

AWS SDK for C++

bug-2-path-planner

An improvement over bug 2 path planning algorithm

chaprotordynamics

Exploring Chaos in the Dynamic Chaplygin Sleigh with Rotor

goldberg_polyhedron

This program makes Goldbergs Polyhedron (Geodesic Sphere of Hex and Pentagons) of given order n.

gstreamer-cheat-sheet

Gstreamer command-line cheat sheet

natural-pattern-adaptation-ca

A repository for the final project in MathBio class, exploring the dynamics of natural pattern adaptation through the lens of a cellular automata model. Contains code, documentation, and resources related to the project.

simulation-of-cable-driven-flexible-manipulators-using-matlab-and-simulink

This repository contains my work on 'Simulations of Cable-Driven flexible Manipulators' during the Tele-Internship at the Department of Bio-medical Engineering, NUS, under the guidance of Dr. Ren Hongliyang.

simulation-of-the-snake-locomotion-mechanisms

Implementation of Snake locomotion mechanisms on the derived Simplified Kinematical Model of discrete Snake Robot in MATLAB.

snake-game-with-realistic-snake-gaits

Simple Snake game using OpenGL C++, including a discrete snake robot model for producing real snakelike movements.

tetra-edm-localizer

Tetrahedron and Euclidean Distance Based Decentralized Relative Localization for Multi-Robot Systems

wavelet-analysis-image-compression-using-discrete-haar-wavelet-transform.

In this project, we will present an example of an orthonormal system on [0,1) known as the Haar system. The Haar basis is the simplest and historically the first example of an orthonormal wavelet basis. Many of its properties stand in sharp contrast to the corresponding properties of the trigonometric basis (Fourier Basis). For example, (1) The Haar basis functions are supported on small subintervals of [0,1), whereas the Fourier basis functions are nonzero on all of [0,1), (2) The Haar basis functions are step functions with jump discontinuities, whereas the Fourier basis functions are C-infinity on [0,1), (3) The Haar basis replaces the notion of frequency (represented by the index n in the Fourier basis) with the dual notions of scale and location (separately indexed by j and k), (4) the Haar basis provides a very efficient representation of functions that consist of smooth, slowly varying segments punctuated by sharp peaks and discontinuities, whereas the Fourier basis best represents functions that exhibit long term oscillatory behavior.

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